A number of methods have been proposed by which to analyze the chord progressions of musical compositions (in what is known as chord progression analysis). Chord progression analysis typically involves analyzing the chord progressions of numerous musical compositions recorded on a personal computer or a portable music player in order to search for desired musical compositions based on the analyzed chord progressions of the compositions.
Usually, the chord progressions of given music compositions are analyzed on the basis of the chords obtained by analyzing the waveforms representative of audio signals constituting the musical compositions in question. More specifically, as shown in FIG. 1, analyzing the waveforms of a musical composition A (waveforms) gives the chord progression of C, F, G and C, in that order. Likewise, analyzing the waveforms of a musical composition B provides the chord progression of CM7, Dm7, G7 and CM7, in that order. A check is then made to determine whether the chord C of the musical composition A is similar to the chord CM7 of the musical composition B. A check is also made to see if the chord progression of C, F, G and C of the musical composition A is similar to the chord progression of CM7, Dm7, G7 and CM7 of the musical composition B.
Some errors are contained in the chord progressions acquired by chord progression analysis. How such errors occur varies depending on the algorithm for determining chords (and their progressions). Illustratively, ordinary chord progression analysis may yield an erroneous chord progression of C, F, G and Cm instead of the correct chord progression of C, F, G and C, as shown in FIG. 2. In this case, the major chord C is mistaken for the minor chord Cm which may well be analyzed as a chord having a totally different musical significance.
In the above example, the so-called chord distance perspective according to traditional music theory cannot be adopted as it is.
In chord progression analysis, it is relatively easy to distinguish between major and minor chords. The difficulty increases—and the precision of analysis drops—when it comes to detecting, say, diverse four-note chords.
Meanwhile, there exist musical composition data creating apparatuses (such as one disclosed in Patent Document 1) which extract the frequency component corresponding to each note from the audio signals representative of musical compositions, detect from the extracted frequency components corresponding to each note a first and a second chord candidate each formed by three frequency components amounting to a high level, and smooth out the progressions of the first and the second chord candidates in order to create musical composition data.    Patent Document 1: Japanese Patent Laid-Open No. 2004-184510